public void saveIndividual(int index, Individual indiv)
{
if(index < 0)
{
individuals[individuals.Length - 1] = indiv;
} else
{
individuals[index] = indiv;
}
}
// Calculate inidividuals fittness by comparing it to our candidate solution
public static int getFitness(Individual individual)
{
int fitness = 0;
// Loop through our individuals genes and compare them to our cadidates
for (int i = 0; i < individual.size() && i < solution.Length; i++) {
if (individual.getGene(i) == solution[i]) {
fitness++;
}
}
return fitness;
}
public Population(int populationSize, bool initialise)
{
individuals = new Individual[populationSize];
if (initialise)
{
for (int i = 0; i<size();i++)
{
Individual newIndividual = new Individual();
newIndividual.generateIndividual();
saveIndividual(i, newIndividual);
}
}
}
// Mutate an individual
private static void mutate(Individual indiv)
{
// Loop through genes
for (int i = 0; i < indiv.size(); i++) {
if (Rnd.NextDouble() <= MutationRate) {
// Create random gene
byte gene = (byte)Math.Round(Rnd.NextDouble());
indiv.setGene(i, gene);
}
}
}
// Crossover individuals
private static Individual crossover(Individual indiv1, Individual indiv2)
{
Individual newSol = new Individual();
// Loop through genes
for (int i = 0; i < indiv1.size(); i++) {
// Crossover
if (Rnd.NextDouble() <= UniformRate) {
newSol.setGene(i, indiv1.getGene(i));
} else {
newSol.setGene(i, indiv2.getGene(i));
}
}
return newSol;
}